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Record W2774887524 · doi:10.1080/10962247.2017.1409294

Protection from wintertime rainfall reduces nutrient losses and greenhouse gas emissions during the decomposition of poultry and horse manure-based amendments

2017· article· en· W2774887524 on OpenAlexafffund
Gabriel Maltais‐Landry, Katarina Neufeld, D. Poon, Nicholas J. Grant, Zoran Nesic, Sean Smukler

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsMinistry of AgricultureGovernment of British ColumbiaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaGovernment of CanadaUniversity of Florida
KeywordsEnvironmental scienceGreenhouse gasAmendmentNutrientManureAgronomyNutrient managementCompostNitrous oxideSoil conditionerAnimal scienceEnvironmental engineeringSoil waterBiologyEcologySoil science

Abstract

fetched live from OpenAlex

Manure-based soil amendments (herein “amendments”) are important fertility sources, but differences among amendment types and management can significantly affect their nutrient value and environmental impacts. A 6-month in situ decomposition experiment was conducted to determine how protection from wintertime rainfall affected nutrient losses and greenhouse gas (GHG) emissions in poultry (broiler chicken and turkey) and horse amendments. Changes in total nutrient concentration were measured every 3 months, changes in ammonium (NH4+) and nitrate (NO3−) concentrations every month, and GHG emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) every 7–14 days. Poultry amendments maintained higher nutrient concentrations (except for K), higher emissions of CO2 and N2O, and lower CH4 emissions than horse amendments. Exposing amendments to rainfall increased total N and NH4+ losses in poultry amendments, P losses in turkey and horse amendments, and K losses and cumulative N2O emissions for all amendments. However, it did not affect CO2 or CH4 emissions. Overall, rainfall exposure would decrease total N inputs by 37% (horse), 59% (broiler chicken), or 74% (turkey) for a given application rate (wet weight basis) after 6 months of decomposition, with similar losses for NH4+ (69–96%), P (41–73%), and K (91–97%). This study confirms the benefits of facilities protected from rainfall to reduce nutrient losses and GHG emissions during amendment decomposition.Implications: The impact of rainfall protection on nutrient losses and GHG emissions was monitored during the decomposition of broiler chicken, turkey, and horse manure-based soil amendments. Amendments exposed to rainfall had large ammonium and potassium losses, resulting in a 37–74% decrease in N inputs when compared with amendments protected from rainfall. Nitrous oxide emissions were also higher with rainfall exposure, although it had no effect on carbon dioxide and methane emissions. Overall, this work highlights the benefits of rainfall protection during amendment decomposition to reduce nutrient losses and GHG emissions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.215
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2017
Admission routes2
Has abstractyes

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